Bioautomation (Oct 2008)

Assessment of the Efficacy of Pulsed Biphasic Defibrillation Shocks for Treatment of Out-of-hospital Cardiac Arrest

  • Jean-Philippe Didon,
  • Vessela Krasteva,
  • Guy Fontaine,
  • Irena Jekova,
  • Manuel Contini,
  • Johann-Jakob Schmid

Journal volume & issue
Vol. 10, no. 1
pp. 59 – 70

Abstract

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This study evaluates the efficacy of a Pulsed Biphasic Waveform (PBW) for treatment of out-of-hospital cardiac arrest (OHCA) patients in ventricular fibrillation (VF). Large database (2001-2006), collected with automated external defibrillators (AED), (FRED®, Schiller Medical SAS, France), is processed.In Study1 we compared the defibrillation efficacy of two energy stacks (90-130-180 J) vs. (130-130-180 J) in 248 OHCA VF patients. The analysis of the first shock PBW efficacy proves that energies as low as 90 J are able to terminate VF in a large proportion of OHCA patients (77% at 5 s and 69% at 30 s). Although the results show a trend towards the benefit of higher energy PBW with 130 J (86% at 5 s, 73% at 30 s), the difference in shock efficacy does not reach statistical significance. Both PBW energy stacks (90-130-180 J) and (130-130-180 J) achieve equal success rates of defibrillation. Analysis of the post-shock rhythm after the first shock is also provided.For Study2 of 21 patients with PBW shocks (130-130-180 J), we assessed some attending OHCA circumstances: call-to-shock delay (median 16min, range 11-41 min), phone advices of CPR (67%). About 50% of the patients were admitted alive to hospital, and 19% were discharged from hospital. After the first shock, patients admitted to hospital are more often presenting organized rhythm (OR) (27% to 55%) than patients not admitted (0% to 10%), with significant difference at 15 s and 30 s. Post-shock VFs appear significantly rare until 15s for patients admitted to hospital (0% to 9%) than for patients not admitted to hospital (40% to 50%). Return of OR (ROOR) and efficacy to defibrillate VF at 5 s and 15 s with first shock are important markers to predict patient admission to hospital.

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